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Python vs Ruby vs Rust: What are the differences?
Introduction:
Python, Ruby, and Rust are three popular programming languages used for web development, among other purposes. While they share similarities in terms of high-level syntax and object-oriented programming, there are key differences between them that set them apart. This article will discuss six significant differences between Python, Ruby, and Rust.
Syntax and Code Readability: Python is known for its simple and readable syntax, making it easy to learn and understand. It uses indentation and whitespace to denote code blocks, which helps maintain a clean and consistent code structure. Ruby, on the other hand, focuses on developer productivity and elegance. It offers a more flexible syntax with a variety of different styles and approaches, allowing developers to write code in their preferred way. Rust, being a systems programming language, has a stricter syntax designed for memory safety and performance. It emphasizes explicitness and enforces strict rules, making it less forgiving but more secure.
Purpose and Use Cases: Python is a versatile language known for its ease of use and is widely used for web development, scientific computing, data analysis, and machine learning. Ruby is known for its focus on developer happiness and is commonly used for web development, especially with the Ruby on Rails framework. It emphasizes productivity and convention over configuration. Rust, on the other hand, is designed for systems programming, emphasizing memory safety, low-level control, and performance. It is often used for creating fast and reliable systems software.
Concurrency and Parallelism: Python has a Global Interpreter Lock (GIL), which limits concurrent execution of multiple threads, making it less suitable for CPU-intensive tasks. However, Python offers tools and libraries like asyncio and multiprocessing to achieve concurrency and parallelism. Ruby, similar to Python, also has a GIL, which restricts true parallel execution. It employs a cooperative threading model with event-driven frameworks like EventMachine for concurrency. Rust, being a systems programming language, allows for fine-grained control over concurrency and parallelism through its ownership and borrowing system, making it suitable for highly concurrent tasks.
Memory Management: Python and Ruby both employ automatic memory management using garbage collection, freeing developers from manual memory management. Python utilizes reference counting for memory management, and in cases where reference cycles exist, it uses a cyclic garbage collector. Ruby uses a tracing garbage collector that tracks object relationships in memory to perform garbage collection. Rust, on the other hand, does not have a garbage collector. It manages memory through its ownership, borrowing, and lifetimes system, ensuring memory safety without sacrificing performance.
Performance: Python and Ruby, being high-level languages, are generally slower than low-level languages like Rust. They prioritize developer productivity over raw performance. However, Python has a vast array of performance optimization tools and libraries, like PyPy and Numba, to improve execution speed. Ruby also provides various performance tuning techniques. Rust, being a systems programming language, is designed for performance-critical applications. Its emphasis on zero-cost abstractions and fine-grained control over memory makes it significantly faster than Python and Ruby.
Community and Ecosystem: Python has a larger and more mature ecosystem compared to Ruby and Rust. It has a wide range of libraries and frameworks available for different use cases, making development faster and more accessible. Ruby, although not as extensive as Python's ecosystem, has a vibrant community and a strong focus on convention over configuration with tools like RubyGems and the Ruby on Rails framework. Rust, being a relatively newer language, has a growing community and ecosystem, with emerging libraries and frameworks that cater to specific use cases.
In summary, Python excels in its simplicity and versatility, Ruby focuses on developer happiness and productivity, and Rust emphasizes memory safety and performance. Python and Ruby have more similar use cases in web development and data analysis, while Rust is suitable for systems programming. Python and Ruby have automatic memory management, whereas Rust relies on its ownership system. Python and Ruby prioritize developer productivity over performance, while Rust strives for both efficiency and safety.
I want to create a mobile-first e-commerce platform app. I think Dart and Flutter is a way for me to build cross-platform apps from a single codebase but I might be wrong so what do you guys think?
I also don't know what to do about the back-end. I mean managing the database of products and users. handing orders and invoices. I think Firebase can be an answer to my problems but how far I can go with firebase and its user authentication and database tools? Just firebase is enough for all my back-end needs?
What suits my needs, a relational database or a non-relational database?
Do I need to learn another programming language for handling back-end, like Python or Go?
I would appreciate your opinion. Thanks
Hi, I have 3 years with Flutter and I can see that Flutter with Firebase will be a good choice for you, Just start with Firebase, it's a little bit expensive when you have a lot of users, but there you will have some money to build your own API using any other language, and here I recommend Elixir or Python.
And about what you need to learn: - Dart - Flutter - State management for Flutter - Firebase
Then you can publish your app finally, and I wish you a happy published app :)
Hello, I am still a student and would like to ask a question. Currently, I am developing in mobile development with Flutter in the frontend and Python in the backend part. Right now I have to make a choice about developing a mobile app or developing a backend to progress more professionally. My questions are as follows:
1) If I prefer the mobile application area, will I only work with the Ui/Ux developer with the front-end and code the designs in Swift Kotlin languages, am I responsible for the back-end software?
2) I have a product that generates new ideas so I like to control the development and work there because the backend is the brain, but are they independent from each other in the backend mobile application? Is the mobile app developer responsible for the backend software?
3) I don't like graphic design because I don't like it if it's not perfect and I get stressed. Am I responsible for the graphic design in the mobile app?
4) Is a mobile app developer also a backend developer?
I know these are very simple questions, but they are very important to me. Thanks for your answers.
Hi Hüseyin! 1-2) In my experience If you are a Mobile Applications Developer you will have the following responsabilities: - Develop (not designing) both functionality and screens of the app you are working - Consume (not develop) third party or self company owned APIs or Backend services - Distribution tasks. - Mantainance tasks. Now, there will always be companies wishing you know the whole thing (ui/ux, backend, frontend, mobile, cd/ci, data science, etc.). And of course it will be helpful for you to know a little bit of the stuff around mobile development, but it's not very common since it's not part of the responsabilities of a mobile app dev.
3) No, you are not responsable for the designs of your application, that's why companies have Product designers, ux designers, ui designers for preparing the screens, logos, color palettes, etc for products. As a developer your job is to see and examine the designs and take them from Figma, InVision, Zeplin, etc to the Code editor.
4) This is the thing, if you are working as a Mobile Developer you might know about Mobile development, not backend, not frontend, not ui ux. BUT if you know a little about backend that might be helpful although backend should not be your responsability.
I hope this makes sense to you. Cheers!
As a mobile developer, I'm usually a member of a larger team and it's usually another person's responsibility to develop the backend/API, and another person's to do the UX/design. Very very few teams use cross-platform tools like Flutter or React Native, because tools like those tend to make mediocre apps that scale poorly and are impossible to debug, so make sure to get familiar with Swift/iOS or Kotlin/Android (or both).
Hi! I think most of your questions led to these answers:
Mobile software developers don't responsible for the back-end part, or even graphic design. Of course, the back-end part should be done by a back-end developer. The graphic design, I'd say that if you work on a start-up, you might be the one who does since there isn't much manpower there, but in the larger company, they would have a designer especially in UI/UX. You'll have a mockup for the application that you need to follow. As a developer, you're expected to code, not design.
I've said that the responsibility isn't yours, but of course, you'll have an advantage over others if you know UI/UX, or back-end as well. That would help you a lot to be a good mobile developer.
Good luck!
Generally speaking, what are the most important things you expect a junior developer to know and be able to do from day 1 in your respective tech stack? Firm grasp of OOP? SQL? MVC? ORM? Algorithms and Datastructures? Understanding CRUD & the request response cycle? Database design? framework familiarity? Postman? Deployment? TDD? Git? Language-specific knowledge? Other things?
Start with building a solid understanding of computer science fundamentals. Understand the basics of building blocks - memory, processing, storage, networking. Understand what CPU bound, memory bound, I/O bound, network bound processes are. Understand the cost of accessing data from Memory vs. Disk vs Network. Understand how multiple CPU threads help in optimizing the performance of a single machine.
Build expertise on a programming language. You may pick any language of your choice. I would recommend starting with Java / Python. Make sure you know one language really well. Build a strong understanding of Data Structures and Algorithms. You should be able to develop an intuition on when to use what. You may practice DS and Algorithm problems, using the language of your choice, on a competitive coding platform (e.g. Leetcode) or by building your own App!
Next, get familiar with basic cloud computing and distributed system concepts. Here is a good resource for that - https://www.youtube.com/watch?v=p7NkTUyEE1o&ab_channel=JeffreyRichter If you understand the computer science fundamentals well, you will be able to apply those concepts here as well.
Hope it helps!
Ability to read code and willingness to try to reason flow of operations and information. Tools and technologies change, one doesn't need to have them in toolbelt from day one. All things you name are relevant in some contexts, so it's not bad to understand them.
Just learn to learn. Learn to search and develop your logical thinking, that's all you need. No books, no deep study of how computers work, just logic and willingness to learn
For me, it is less of a specific technology you know (although I would prefer you have some knowledge of some of my team stack). It is more the way you get into a problem, the eagerness to learn more, the true sincerity to say "I don't know", the open mind to find solutions in different ways and the "Yes we can" mentality no matter how hard it is.
Most employers don't expect from you to know how to implement CI/CD or any other funcy stuff. As junior developer you should focus on building a good toolset of good software practices & principles. Your soft skills are important as well. Learn about soft skills. Be eager to learn, be humble and show you talent and your creativity through your work. If you want to become a good developer ( at first) and a star engineer (at a later stage) then computer programming (coding) is your number one priority . Coding is like painting. Putting aside your talent, you have to practice a lot and improve your outcome each time. As junior developer you can learn how to write good code by studying existing code found in public git repositories (i e , github). As junior developer you should study some good software principles (i.e., DRY, KISS, YAGNI) and always recall them each time you write software code. As junior developer you should learn about coding standards and conventions. You will have to follow to your company's coding conventions (soon or later) as well as you will realize that you have to write code cosistent to the existing code base. At the end of the day, code consistency matters a lot. You have to improve your code day by day. If you manage to follow some good software practices you will find out that you will need an ORM to work with your database. Then you will realize that you need the X web framework to build your REST API etc. To sum up, you will start building a toolset with a single programming language and some good software practices & principles and then you will put new tools in it day-by-day.
Hey there, we are looking to develop our own layer 1 blockchain. We're splitting the responsibilities for origination, clearing, and settlement across three independent but cooperating node networks. We've gotten our Proof of Concept up using Ruby on Rails for the nodes, you can see it as the attached link. So far, so good. Now we are looking to convert it into a distributable and are trying to figure out which language is the best for this.
Essentially our needs from the language are: solid networking tools and speed, very fast execution of basic actions, some parallel execution, and able to compile the end product into an easy to distribute and use package for end users.
I was learning Rust, but I have a healthy amount of experience with Swift and right now, it's only me coding. I've only done iOS coding, but have built a fintech app from scratch that's now in the app store so I'm pretty familiar with the language and its benefits. Haven't experimented with Vapor or any of the application development tools, and I wanted to know if it is a crazy idea to develop a blockchain node in Swift instead.
Pick Rust. Rust can provide all what you need and has been a major language in blockchain/cryptocurrency industry. Swift is slower than Rust and does not have such support in the networking and domain field. Swift tooling is great only on macOS, therefore you are likely to have troubles on other platforms.
You can use swift of course. It’s more of a question of being performant.
You really want to try some basic operations and find what’s most performant for you.
Rust is wonderful for cloud applications requiring heavy concurrency, it has compile time checking for such things.
Go and C++ could be more performant in your case. Swift is really quite an obtuse language, with a lot of features, some which may complicate your implementation.
Also, you want to consider the market of developers who could help build it. If you use Go or C++ there is a larger collection of people who know the languages than there is with swift.
Hi! I'm currently studying Flutter for mobile apps, but I also have a demand to automate some tasks on the web and create backends' for my apps, so thinking about which one of those could be better? Considering the performance and how easy it's to learn and create stuff? (I'm already familiar with .NET stack but want something more "simple" to write)
Definitely Python. Lots of libraries, dead simple syntax. Lots of code examples and reference projects. Elixir is pure functional and takes time to grasp the concepts. Go is great, with simple syntax and performant runtime, but more strict as it is statically typed. For quick coding, nothing beats Python. As you come from .net I’d consider similar approach and be considering Java with SpringBoot as it makes Java faster and much more fun to code web servers
Elixir really has a good performance for the web (and in general). Its framework Phoenix for the web is a great tool, easy to install and to use, with features for websockets (and Pub/Sub) or LiveView to write reactive and real time app with only HTML (and Elixir) so basically everything is in one place
It can take some time to learn a few things in Elixir but I really think it's worth it, and it's very easy to go distributed and concurrent with Elixir. Also it's easier to code quickly with some features like the pattern matching or some operators like the pipe or the capture one
And in the case you need it you can still connect and interface Python and Elixir pretty quickly, and now Elixir has a lot of different frameworks : web, embedded or even neural networks now
Never went far with Go but I have some trouble with its syntax, I find it a bit messy
I don't have a lot of experience with the web with Python but I don't have a good experience with the little I did
Judging your previous experience we will benefit from Golang in terms of portability and speed. If you want to go simplier use Python. If it's only scripts use Python.
Hey Vitor, You can use Node and Express JS to create a backend for your app. You can create REST APIS to connect your front end with the backend. It is a very simple and scalable solution for building backend web apps.
I'm making my university community web service with a team. (6 members myself included)
And we decided to use JavaScript, HTML, CSS (for sure, it's the basic of websites) but couldn't decide for the back end part.
There are tons of languages, tools, etc., but I'm really new to programming, so I'd like to get some help to figure out what tools we need.
So my question is this: are there any good examples of web community services we can mimic the tools or get an insight from them?
Since you're following Python, I would recomend using Django as your main back-end language. If you know Python it would be a great experience. Django is well documented on their official website: https://www.djangoproject.com/ I would also use React for front-end as well. Also this article is worth reading, I think progressive web app is something worth learning these days: https://web.dev/progressive-web-apps/ Hope that helps :)
Since your team is already using JavaScript, there's a great number of examples for backend services written with NodeJS. I'd recommend using Firebase, or any backend as a service (you can use that term to find alternatives), for setting up your backend as it is much easier for newer people to understand and lets you focus on your core application logic, and not provisioning servers, databases, etc.
Since you're team is already using JavaScript, there are alot of examples and open source projects written with NodeJs, so I preffer this language in your backend application and also I am recommended using Mongo DB with It for saving data in it, and also for your frontend application I am recommanded using VueJs.
Since you are already using JavaScript on the front end it would be easy to adopt the MERN (MongoDB, Express, React, NodeJS) stack which s all javascript based making it easy to transfer knowledge with the backend and front end
Kindly I don't find any help that solve this mystery I need more help if it will happen
Make it simple, most of projects doesnt need a AI, ML or big algorithms. If your project just serving end users take it to the web ready compatible. (Javascript, .Net, PHP Laravel)
Hello, I am interested in learning how to program. I am a beginner, and many articles saying I should go with Python if I am new to programming. I considered Lua a long time ago, but for my career, I believe major programming languages should be better for me. I'm considering Python at this moment, but if you have other tools I should use, let me know.
Although Lua is a very simple,efficient, elegant and welcoming language, Python is extremely versatile. Therefore, if you want to get into programming without a defined direction, Python is the way to go. It has a lot of libraries, the ability to do anything and it is closer to other languages than Lua is (yeah I know about Lua and C, but from a learner's point of view, it makes sense). Additionally, Python will be a marketable skill, but I for one have not yet seen job offers for Lua devs.
The language you choose is also dependant on the type of career / area of programming you wish to focus on: Web Based and mobile applicaitons I would lean towards Java, PC Applications I tend to like C#, Embedded industry C, C++
my advice , you should answer me for this question, what do you like to work: web base or mobile native or cross platform. if you like web base you should choose PHP or ASP.net or Node.js or if you like mobile native you should decide Android or IOS platform and else if you like cross platfrom you should learn Flutter with dart language. thanks
Hey, 👋
My name is Brayden. I’m currently a Frontend React Developer, striving to move into Fullstack so I can expand my knowledge.
For my main backend language, I am deciding between Python, Rust, and Go. I’ve tried each of them out for about an hour and currently, I like Python and Rust the most. However, I’m not sure if I’m missing out on something!
If anyone has advice on these technologies, I’d love to hear it!
Thanks.
Rust is still in low demand. It's a great language but you'll have a hard time finding jobs. Go is the mix of both Rust and Python. Great language with modern features, fast, scalable, fun to write, and at the same time it has high demand (not as much as python).
Python on the other hand is a language that you can't go wrong with. Look around you and see what your job market prefers. If there isn't much difference to you personally, pick the one with more demand.
All of these are solid options, however considering your expertise currently, I would probably suggest Node.JS considering your past experience with JS. However Python offers a similar development environment to JS in my opinion, and Go is a good sort of intermediate between Rust and Node.JS and Python. It's fast, but not as fast as Rust, and offers a development experience that combines C-styled languages (like Rust), and Python-y languages... So: Rust for the fastest, Node for familiarity, Python for ease of development, and Go for a good middle ground. I have used all in personal projects... If you use Go, I suggest a easy to use web server framework like Fiber.
Rust is a challenging choice, but worth to be chosen. It has strong memory-safety and type-safety, this gives you no bother about those errors. However, static typing languages often slow our developing speed down in early stage. In that case, it's effective to write prototype in an easy language like Python, and rewrite it in a hard language. It's important not to be afraid to throw away first code you write.
The other answers are excellent, but I want to be a bit of a contrarian and say you should learn Rust. While the number of jobs for it are (relatively) low(er), it is certainly expanding and you'd be surprised at which companies do use Rust (Discord, for example, is starting to move away from Golang to Rust!).
But the main reason is that learning Rust itself will teach you a lot about systems design (/backend) because of its borrow checker. You can try out a lot of ideas and make a lot mistakes and the borrow checker will always be there guide you to a better solution (thereby teaching you in the process).
Also, I wouldn't underestimated how important managing memory (and memory safety) is. While Golang is great in some ways, it doesn't protect you from pushing memory leaks into production. And eventually you'll come upon a scenario where you'll have to make your Python code run faster and the optimizations you'd have to do won't look pretty (or be very Pythontic).
And Rust is freakin fast! If you have Rust, you wouldn't need any other language for the backend (or any other systems level code). Check this blog post: https://blog.discord.com/why-discord-is-switching-from-go-to-rust-a190bbca2b1f?gi=dd8bc5d669d. Discord found that even after spending months optimizing Golang code it still wasn't fast enough. But unoptimized, first-draft Rust code was (is) faster by an order of magnitude!
Hi
I want to build a tool to check asset availability (video, images, etc.) from third-party vendors. These vendors have APIs. However, this process should run daily basis and update the database with the status. This is a kind of separate process. I need to know what will be the good approach and technology for this?
hi - I think this depends on how you want to provide the information to the user. If you want to build a Wordpress-plugin: PHP If you want to build your own website: Python+Django / PHP / JavaScript+Node.js As Desktop application?
for what technologies you should use, this is depend on what technology do you prefer? your should think best structuing for your code because each API vendor has different to a nother one so it's better no merege code vendores together. your code must be using SOLID principle pattern and some design pattern such as Factory Pattern
The major advantage of Go is that you can run queries in parallel. Fire off a Go thread for each vendor and each thread can check the availability of assets from a specific vendor and update the database. Go supports hundreds of threads with ease.
your decision depend on what language do you know. if you know php you can use laravel framework
Hi, I would recommend Go because of strongly-typed nature which makes a developer more productive as it is less error prone compared to the other dynamic-typed language. Go also has cron-job library(powered by goroutines) that can help with your automated tasks.
I was thinking about adding a new technology to my current stack (Ruby and JavaScript). But, I want a compiled language, mainly for speed and scalability reasons compared to interpreted languages. I have tried each one (Rust, Java, and Kotlin). I loved them, and I don't know which one can offer me more opportunities for the future (I'm in my first year of software engineering at university).
Which language should I choose?
I will highly recommend Kotlin. I have worked with all three intensely and so far the development speed and simplicity is the best with Kotlin. Kotlin supports coroutines out of the box. Now, it isn't something that can't be implemented in other languages but Kotlin makes it super easy to work with them. Kotlin has a bit of learning curve, so, by the time you can actually use it idiomatically chances are that you will get proficient in Java too. But once you get it, you get it, then there is no other language ;) Kotlin is backed by Google and Jetbrains team so you can expect latest programming features and good community support.
It depends on which level and use cases you prefer to work at. Close to the machine? Rust is great but if you need to find more job opportunities, then take C/C++. Java has many job positions but I suggest Kotlin over it. Think about it as a better Java, but fewer job positions. Do you want to do your own projects? So a productive language like Ruby is way better. Like to program front-end apps? Take JS. Find your passion.
I'd say Rust's knowledge will be more valuable in comparison. You can work in Blockchain development, compile to WASM (WebAssembly). There is a new JavaScript/TypeScript runtime named Deno (by the creator of Node.js) that has its backend in Rust.
If you want a compiled language then go for Rust. It takes a certain mindset to get your head around its memory management system and the way it handles "borrowed" memory. However, it will generate blindingly fast code that you can cross-compile for other platforms. As a systems programming language I highly recommend it. Take time and learn it.
Java is only compiled to bytecode, not to machine code. So it executes in the Java Virtual Machine. DOn't think that its not fast, because the latest incarnation are very fast indeed. For most practical purposes, users of your code won't notice any difference. There are a heck of a lot of features in Java that you either have to import via crates in Rust, or write yoursef. So productivity-wise, Java may well beat Rust.
Kotlin is a Java-lookalike. It's a nice, and succinct version of Java and is totally interoperable. But its a bit niche, and for me it fails because my dev environment of choice (Spring Tool Suite) doesn't really play well with Kotlin. To use it you would be well advised to use iDeaj. I have used kotlin, and I like it, but not enough to ditch all my Java code.
Other contenders, depending on your platform of choice are Golang, C, C++, and C# (available as Mono on Linux systems).
I use Rust and Java and if you need a compiled language I recommend Rust.
As you certainly know, there are languages that compile in meta-code for Virtual Machines (Java, C#, Kotlin) and languages that compile in Machine Language (Go, Rust). Apart specific domains (blockchain, IoT embedded software, AI, cloud) almost no-one uses languages that compile in machine language, for a series of reason, most of all security and portability. So, if you are going to learn for business go with Kotlin - Java is a bit ancien regime. If you seriously need to learn a language that compiles in ML - for example you will code for IoT - go with Go - or Rust - but keep in mind that Rust is much less used than Go. PS: Kotlin also compiles in ML, but I would choose a language designed for that, instead of one that compiles "also" in ML. PPS: Some Virtual Machines - ie: GraalVM - allow you to compile Java in ML. The world of IT is beautiful.
I would go with Kotlin. It is pretty hyped currently.
You can use Kotlin for a lot of application types. To name some:
- Kotlin Multiplatform with Gradle
- Ktor (https://ktor.io)
- Spring Boot
- Kotlin JS (as you already know Javascript, you might like this one)
The code is also really concise, readable and modern. It also provides many features that you will find in many other programming languages.
I'd recommend you to take a look at Java and Kotlin, the first due to the number of companies that actively use it in your products. Kotlin is gaining adept since it is fully compatibly with the Java ecosystem but usually requires less code to do the same (ignoring other benefits of the language). Another benefits of the Kotlin is that it is in fact multiplatform, where you could use the same syntax to code for mobile, web and backend applications. The drawback of Kotlin, is the number of open jobs that exists currently compared to Java, but I pretty sure that it will change in the near future.
All those are nice languages, but Rust is harder to learn properly and has a smaller ecosystem. If you want to work in system programming (like hardware drivers) Rust is probably your choice. Otherwise, Java/Kotlin ecosystem is much larger and gives much more possibilities (maybe excluding low-level system programming).
When talking about Kotlin and Java, both are good. But Kotlin, again, gives much more opportunities. Kotlin-JS gives you browser applications, Kotlin-Native allows to compile to native application (and interop with them). Kotlin-WASM will be available shortly. Rust is better than Kotlin-Native for native development tight now, but not by far and it makes sense only if you are focusing only on native development.
Coming from a C/C++ background, I picked up PHP 20 years ago. Today, the language is still in constant evolution while still having a stable base. It powers all of my backend project. It is fast to prototype and get started, and is supported almost everywhere.
Python and Node.js do not provide anything that PHP cannot already offer, so there is no point for me to switch to those language. Mature framework like Laravel provides real ease and speed of development to kick-start any new web project, be it a simple API or a robust ERP running on server-less architecture. There are libraries available for machine learning, crypto, web3 and pretty much anything you can think of.
We chose Rust for our web API because the Warp crate makes it easy to compose high-performance and asynchronous APIs. Rust allows us to achieve high development velocity because it provides zero-cost abstractions and enforces strict type and memory-safety checks with high quality and actionable error messages.
Python will be used in order to train machine learning models from our data. We chose python for this task because it is the most common language for machine learning. It has very performant libraries like numpy and scikit-learn that provide functionality for manipulating data and creating models that you cannot get in other languages like JavaScript and Java. Additionally, it is the most familiar language for us to use for machine learning because almost every machine learning course teaches ml using python.
Javascript will be used for both our frontend and backend on the web service. JavaScript is ubiquitous as the language to use for the frontend. For the backend, we decided to create our server using JavaScript because of its easy setup; using Express we can create a server in just a few short lines of code. It is simple not only to run the server locally, but to host it as well because any major service will support the language. JavaScript is a simple language to code in and familiar among our team members, so using it will help speed up development. Using JavaScript allows us to use NodeJS and npm, so we can use packages to easily set up the server, connect to a database and other convenient utilities. We also considered Python for our server. It is also very simple to create a server in Python, especially using flask. However, the extra familiarity with the JavaScript language and the ease of using packages were enough for us to pick JavaScript as our language of choice.
MACHINE LEARNING
Python is the default go-to for machine learning. It has a wide variety of useful packages such as pandas and numpy to aid with ML, as well as deep-learning frameworks. Furthermore, it is more production-friendly compared to other ML languages such as R.
Pytorch is a deep-learning framework that is both flexible and fast compared to Tensorflow + Keras. It is also well documented and has a large community to answer lingering questions.
Python: The top language in machine learning area because of the various open-source libraries. Our company will rely on open-source libraries for development as well.
Amazon EC2: Training machine learning model needs to be running on independent 3rd party computing resources. AWS EC2 can provide a variety of virtual computing resources based on what users need.
React+Javascript: React is popular and everyone in the team is familiar with it. React is an open-source JavaScript library that is used for building user interfaces specifically for single-page applications.
ExpressJS: Everyone in the team has used expressJS for development. It can create server-side web applications faster and smarter.
Amazon RDS: relational database service and free to use
Postman: Tool for the team to test API endpoint.
Circle CI: is lightweight and open. Therefore for faster deployment jobs, one can execute their codes on CircleCI as it deploys on scalable and robust cloud servers.
Docker: Easily pack, ship, and run any application as a lightweight, portable, self-sufficient container, which can run virtually anywhere
Github+Git: Julian is from Github so no other choice for us 😎
Slack: Everyone likes it and it's free
Python: Top one language in machine learning area because of the various open source libraries. Our company will rely on the open source libraries for development as well.
Amazon EC2: Training machine learning model needs to be ran on independent 3rd party computing resources. AWS EC2 can provide variety of virtual computing resources based on what users need.
React+Javascript: React is popular and everyone in the team is familiar with it. React is an open-source JavaScript library that is used for building user interfaces specifically for single-page applications.
ExpressJS: Everyone in the team has used expressJS for development. It can create server-side web applications faster and smarter.
Amazon RDS: relational database service and free to use
Postman: Tool for the team to test API end point.
Circle CI: is lightweight and open. Therefore for faster deployment jobs, one can execute their codes on CircleCI as it deploys on scalable and robust cloud servers.
Docker: Easily pack, ship, and run any application as a lightweight, portable, self-sufficient container, which can run virtually anywhere
Github+Git: Julian is from Github so no other choice for us 😎
Slack: Everyone likes it and it's free
2 major challenges for which JS comes as a handy tool, 1st its integration with AWS SDK was at par as Python and .net and the solution comes to hand with the reverse proxy solutions for the application to be running as an instance taking the situation of inside organization demography of resources expertise over the technology.
I had a goal to create the simplest accounting software for Mac and Windows to help small businesses in Canada.
This led me to a long 2 years of exploration of the best language that could provide these features:
- Great overall productivity
- International wide-spread usage for long-term sustainability and easy to find documentation
- Versatility for creating websites and desktop softwares
- Enjoyable developper experience
- Ability to create good looking modern UIs
- Job openings with this language
I tried Python, Java, C# and C++ without finding what I was looking for.
When I discovered Javascript, I really knew it was the right language to use. Thinking of this today makes me realize even more how great a decision this has been to learn, use and master Javascript. It has been a fun, challenging and productive road on which I am still satisfied.
Obviously, when I refer to Javascript, it is not without implying the vast ecosystem around it. For me, JS is a whole universe in which almost every imaginable tools exist. It's awesome - for real. Thanks to all the contributors which have made it possible.
To be even clearer about how intense I am with Javascript, let's just say that my first passion was music. Until, I find coding with Javascript! Yep, I know!
So in conclusion, I chose Javascript because it is versatile, enjoyable, widely used, productive for both desktop softwares and websites with ability to create modern great looking user interfaces (assuming HTML and CSS are involved) and finally there are job openings.
#rust #elixir So am creating a messenger with voice call capabilities app which the user signs up using phone number and so at first i wanted to use Actix so i learned Rust so i thought to myself because well its first i felt its a bit immature to use actix web even though some companies are using Rust but we cant really say the full potential of Rust in a full scale app for example in Discord both Elixir and Rust are used meaning there is equal need for them but for Elixir so many companies use it from Whatsapp, Wechat, etc and this means something for Rust is not ready to go full scale we cant assume all this possibilities when it come Rust. So i decided to go the Erlang way after alot of Thinking so Do you think i made the right decision?Am 19 year programmer so i assume am not experienced as you so your answer or comment would really valuable to me
Pros of Python
- Great libraries1.2K
- Readable code962
- Beautiful code847
- Rapid development788
- Large community690
- Open source438
- Elegant393
- Great community282
- Object oriented272
- Dynamic typing220
- Great standard library77
- Very fast60
- Functional programming55
- Easy to learn49
- Scientific computing45
- Great documentation35
- Productivity29
- Easy to read28
- Matlab alternative28
- Simple is better than complex24
- It's the way I think20
- Imperative19
- Free18
- Very programmer and non-programmer friendly18
- Powerfull language17
- Machine learning support17
- Fast and simple16
- Scripting14
- Explicit is better than implicit12
- Ease of development11
- Clear and easy and powerfull10
- Unlimited power9
- It's lean and fun to code8
- Import antigravity8
- Print "life is short, use python"7
- Python has great libraries for data processing7
- Although practicality beats purity6
- Now is better than never6
- Great for tooling6
- Readability counts6
- Rapid Prototyping6
- I love snakes6
- Flat is better than nested6
- Fast coding and good for competitions6
- There should be one-- and preferably only one --obvious6
- High Documented language6
- Great for analytics5
- Lists, tuples, dictionaries5
- Easy to learn and use4
- Simple and easy to learn4
- Easy to setup and run smooth4
- Web scraping4
- CG industry needs4
- Socially engaged community4
- Complex is better than complicated4
- Multiple Inheritence4
- Beautiful is better than ugly4
- Plotting4
- Many types of collections3
- Flexible and easy3
- It is Very easy , simple and will you be love programmi3
- If the implementation is hard to explain, it's a bad id3
- Special cases aren't special enough to break the rules3
- Pip install everything3
- List comprehensions3
- No cruft3
- Generators3
- Import this3
- If the implementation is easy to explain, it may be a g3
- Can understand easily who are new to programming2
- Batteries included2
- Securit2
- Good for hacking2
- Better outcome2
- Only one way to do it2
- Because of Netflix2
- A-to-Z2
- Should START with this but not STICK with This2
- Powerful language for AI2
- Automation friendly1
- Sexy af1
- Slow1
- Procedural programming1
- Ni0
- Powerful0
- Keep it simple0
Pros of Ruby
- Programme friendly606
- Quick to develop537
- Great community491
- Productivity469
- Simplicity432
- Open source274
- Meta-programming235
- Powerful208
- Blocks157
- Powerful one-liners140
- Flexible70
- Easy to learn59
- Easy to start52
- Maintainability42
- Lambdas38
- Procs31
- Fun to write21
- Diverse web frameworks19
- Reads like English14
- Makes me smarter and happier10
- Rails9
- Elegant syntax9
- Very Dynamic8
- Matz7
- Programmer happiness6
- Object Oriented5
- Friendly4
- Fun and useful4
- Generally fun but makes you wanna cry sometimes4
- Elegant code4
- There are so many ways to make it do what you want3
- Easy packaging and modules3
- Primitive types can be tampered with2
Pros of Rust
- Guaranteed memory safety145
- Fast132
- Open source88
- Minimal runtime75
- Pattern matching71
- Type inference63
- Concurrent57
- Algebraic data types56
- Efficient C bindings47
- Practical43
- Best advances in languages in 20 years37
- Safe, fast, easy + friendly community32
- Fix for C/C++30
- Stablity25
- Zero-cost abstractions24
- Closures23
- Extensive compiler checks20
- Great community20
- Async/await18
- No NULL type18
- Completely cross platform: Windows, Linux, Android15
- No Garbage Collection15
- High-performance14
- Great documentations14
- Super fast12
- High performance12
- Generics12
- Guaranteed thread data race safety11
- Safety no runtime crashes11
- Macros11
- Fearless concurrency11
- Compiler can generate Webassembly10
- Helpful compiler10
- RLS provides great IDE support9
- Prevents data races9
- Easy Deployment9
- Painless dependency management8
- Real multithreading8
- Good package management7
- Support on Other Languages5
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Cons of Python
- Still divided between python 2 and python 353
- Performance impact28
- Poor syntax for anonymous functions26
- GIL22
- Package management is a mess19
- Too imperative-oriented14
- Hard to understand12
- Dynamic typing12
- Very slow12
- Indentations matter a lot8
- Not everything is expression8
- Incredibly slow7
- Explicit self parameter in methods7
- Requires C functions for dynamic modules6
- Poor DSL capabilities6
- No anonymous functions6
- Fake object-oriented programming5
- Threading5
- The "lisp style" whitespaces5
- Official documentation is unclear.5
- Hard to obfuscate5
- Circular import5
- Lack of Syntax Sugar leads to "the pyramid of doom"4
- The benevolent-dictator-for-life quit4
- Not suitable for autocomplete4
- Meta classes2
- Training wheels (forced indentation)1
Cons of Ruby
- Memory hog7
- Really slow if you're not really careful7
- Nested Blocks can make code unreadable3
- Encouraging imperative programming2
- No type safety, so it requires copious testing1
- Ambiguous Syntax, such as function parentheses1
Cons of Rust
- Hard to learn28
- Ownership learning curve24
- Unfriendly, verbose syntax12
- High size of builded executable4
- Many type operations make it difficult to follow4
- No jobs4
- Variable shadowing4
- Use it only for timeoass not in production1